The goal of this project is to develop a next-generation fracture detection and characterization technology for producing natural gas from low permeability formations.

Performer

University of Texas at Austin Bureau of Economic Geology

Location:
Austin, Texas 78713

Background

The research proposed here combines a new seismic shear wave (s-wave) imaging concept for 3-1 acquisition geometries with a new microfracture based analysis technique of oriented sidewall cores. This is the next-generation technology for detecting and characterizing subsurface fractures. The seismic component of this research is an approach that abandons the conventional industry practice of using Alford rotation to create fracture-sensitive s-wave images in 3-D geometries. Our investigation of existing industry practice leads us to conclude that data processing techniques, that separate s- waves into fast and slow modes in 3-D geometries, are fundamentally flawed. We propose that a new data- processing model, based on SH and SV mode concepts, be used in 3-D imaging of s-waves. This model is leading us to a new data-processing technology for detecting fractures when s-waves are recorded by 3-1 seismic templates. The seismic calibration portion of the research relies on collecting sidewall cores and then observing and classifying micro-fractures to calibrate fracture-sensitive seismic attributes.

Amplitude Contours

Impact

This research used a new seismic shear-wave (s-wave) imaging concept for 3-D acquisition geometries for detecting and characterizing subsurface fractures. An unexpected change in an industry partner resulted in no core being available for microfracture studies. A new data-processing model based on SH and SV mode concepts were used for 3-D imaging of shear waves. Seismic data acquired across a fractured carbonate reservoir system illustrate how 3 component 3-D seismic data can provide useful information about fracture systems. Fast-S and slow-S data are used to illustrate how these effects can be analyzed in the prestack domain to recognize fracture azimuth, and then demonstrate how fast-S and slow-S data volumes can be analyzed in the post-stack domain to estimate fracture intensity.

Accomplishments (most recent listed first)

The key observations from the study were:

When a seismic propagation medium has a reasonable amount of anisotropy, converted-SV wavefields bifurcate into fast-S (S1) and slow-S (S2) modes.

S1 and S2 azimuths can be estimated in the prestack domain by creating common-azimuth trace gathers of radial and transverse components of the reflected P-SV wavefield.

Fracture orientation coincides with the azimuth in which there is the maximum reflectivity of the radial component of the P-SV wavefield. This concept was verified by well control.

Using prestack determinations of S1 and S2 azimuths, 3C3D data can be processed to generate independent S1 and S2 data volumes.

Attributes extracted from S1 and S2 data volumes can be used to infer key fracture properties, such as fracture orientation and relative fracture intensity.

The ratio of S1-to-S2 reflection amplitudes indicated where fracture intensity for one targeted reservoir interval increased and decreased in a relative sense. This concept was supported by anecdotal information provided by the field operator.